Computational Linguistics

Presented by: Mbarek Elfarhaoui

Outline I. Introduction

II. Definition of CL

III. Origins

VI. Areas of Application

V. Approaches in CL

IV. Conclusion

I. Introduction

The Association for Computational linguistics defines CL as

the scientific study of language from a computational perspective. Computational linguists are interested in providing computational models of various kinds of linguistic phenomena.

Work in computational linguistics is in some cases motivated from a scientific perspective in that one is trying to provide a computational explanation for a particular linguistic or psycholinguistic phenomenon.

II. Definition of CL

Computational linguistics is the application of linguistic theories and computational techniques to problems of natural language processing.

Grishman (1986) defines Computational linguistics as the study of computer systems for understanding and generating natural language.

Structure of linguistic science.

The purpose of CL is to develop applications that deal with computer tasks realted to human language, like development of software for grammar correction, word sense disembiguation, compilation of dictionaries and corpora, automatic translation from one language to another, etc.

III.origins Computational linguistics originated in the

United States in the 1950s to use computers to automatically translate texts from foreign languages, particularly Russian scientific journals into English. CL was born as the name of the new field of study devoted to developing algorithms and software for intelligently processing language data.

Computers were first used for automatic/ mechanical translation.Then, their use was extended to deal with linguistics.

In order to translate a text, it was observed that one had to understand the grammar of both languages, including morphology, syntax, semantic, pragmatics, ..etc. One of the earliest and best known examples of a computer program is the s-called the ELIZA program developed by Joseph Weizenbaumat in 1966.

VI. Approaches in CL Rule-Based Systems

Explicit encoding of linguistic knowledge

Usually consisting of a set of hand-crafted,

grammatical rules

Require considerable human effort

Often fail to reach sufficient domain coverage

Data-Driven Systems

Implicit encoding of linguistic knowledge

Often using statistical methods or machine learning

methods

Require less human effort

Are data-driven and require large-scale data source

V. Application Areas

machine translationspeech recognitionman-machine interfacesintelligent word processing: spelling

correction,grammar correction

One of commercial translators.

document management

find relevant documents in collections

catch plagiarism

extract information from documents

classify documents

summarize documents

summarize document collections

Classifier program determines the main topics of a document.

Conclusion

Nowdays research within the scope of CL is done at computational linguistics departments, CL laboratories, computer science departments, and linguistics departments.

Bolshakov,Igor A., Gelbuck,Alexder.(2004).Computational Linguistics: Models, Resources, Applications.

 Aronoff, Mark and Miller,Janie Rees-. (2001). The Handbook of Linguistics. Blackwell Publishers.

Brown, Keith. (1991). Encyclopedia of Language and Linguistics. Second Edition. Volume I.

References